• Journal of the Korean Society of Visualization
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• v.3 no.1
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• pp.71-77
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• 2005

Information on temporal evolution of whole velocity fields are essential for physical understanding of a complicated turbulent flow. Due to advances of high-speed imaging technique, laser and electronics, high-speed digital cameras and high-repetition pulse lasers are commercially available in nowadays. A dynamic PIV system that can measure consecutive instantaneous velocity field with 1K$\times$ 1K pixels resolution at 1 fps was developed. It consists of a high-speed CMOS camera and a high-repetition Nd:YLF pulse laser. Theoretically, it can capture velocity fields at 20 fps with a reduced spatial resolution. In order to validate its performance, the dynamic PIV system was applied to a turbulent jet of which Reynolds number is about 3000. The particle images of 1024$\times$512 pixels were captured at a sampling rate of 4 KHz. The dynamic PIV system measured successfully the temporal evolution of instantaneous velocity fields of the turbulent jet, from which spectral analysis of turbulent structure was also feasible.

• Journal of International Society for Simulation Surgery
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• v.4 no.1
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• pp.21-23
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• 2017

Purpose In this paper, we proposed alternate neighborhood system and reverse spread-direction approach for accurate and fast cellular automata-based image segmentation method. Materials and Methods On the basis of a simple but effective interactive image segmentation technique based on a cellular automaton, we propose an efficient algorithm by using Moore and designed neighborhood system alternately and reversing the direction of the reference pixels for spreading out to the surrounding pixels. Results In our experiments, the GrabCut database were used for evaluation. According to our experimental results, the proposed method allows cellular automata-based image segmentation method to faster while maintaining the segmentation quality. Conclusion Our results proved that proposed method improved accuracy and reduced computation time, and also could be applied to a large range of applications.

• JSTS:Journal of Semiconductor Technology and Science
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• v.3 no.4
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• pp.175-180
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• 2003

In this paper, we present a new method for early depth test for a 3D rendering engine. We add a filter stage to the rasterizer in the 3D rendering engine, in an attempt to identify and avoid the occluded pixels. This filtering block determines if a pixel is hidden by a certain plane. If a pixel is hidden by the plane, it can be removed. The simulation results show that the filter reduces the number of pixels to the next stage up to 71.7%. As a result, 67% of memory bandwidth is saved with simple extra hardware.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2400-2419
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• 2014

Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.

• Journal of the Korean Society of Visualization
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• v.6 no.2
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• pp.20-27
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• 2008

The color sorting technique utilizing the image processing method is very applicable tool to analyze motion of a free-falling object in many agricultural and industrial research fields. In the present study, we have developed an image processing system and algorithm to sort good quality rice grains effectively from the bad ones. The system employs a high speed rate line-scan CCD camera with 2K-pixels and worked with a high speed DSP and FPGA in-line. It can accumulate acquired line-scan image data and visualize each grain image clearly. As a result, we can easily calculate the number of pixels occupied by grain(=grain size), gray level and its correct position by visualizing grain images rapidly.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.18-21
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• 2008

Lee (2008) proposed the pansharpening method to reconstruct at the higher resolution the multispectral images which agree with the spectral values observed from the sensor of the lower resolution values. It outperformed over several current techniques for the statistical analysis with quantitative measures, and generated the imagery of good quality for visual interpretation. However, if a small object stretches over two adjacent pixels with different spectral characteristics at the lower resolution, the pixels of the object at the higher resolution may have different multispectral values according to their location even though they have a same intensity in the panchromatic image of higher resolution. To correct this problem, this study employed an iterative technique similar to the image restoration scheme of Point-Jacobian iterative MAP estimation. The effect of pansharpening on image segmentation/classification was assessed for various techniques. The method was applied to the IKONOS image acquired over the area around Anyang City of Korea.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.371-374
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• 2008

In very high-spatial resolution remote sensing imagery, it is difficult to extract the feature information of various objects because of occlusion and shadows. Moreover, various and feeble information within shadows can be of use in GIS-based applications and remote sensing analysis. In this paper, we developed a radiometric restoration method for shadow areas using KOMPSAT-2 satellite image. After detecting the shadow, non-shadow pixels nearby are extracted using a morphological filter. An iterative linear regression method is applied to calculate the relationship between shadow and non-shadow pixels. The shadows are restored by the parameters of the linear regression algorithm. Tests show that recovery of shadowed areas by our method leads to improved image quality.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.52-57
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• 2007

In this paper we proposed multi-directional matching windows combined by multi-dimensional feature vector matching, which uses not only intensity values but also multiple feature values, such as variance, first and second derivative of pixels. Multi-dimensional feature vector matching has the advantage of compensating the drawbacks of area-based stereo matching using one feature value, such as intensity. We define matching cost of a pixel by the minimum value among eight multi-dimensional feature vector distances of the pixels expanded in eight directions having the interval of 45 degrees. As best stereo matches, we determine the two points with the minimum matching cost within the disparity range. In the experiment we used aerial imagery and IKONOS satellite imagery and obtained more accurate matching results than that of conventional matching method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.91-98
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• 1997

In this paper, a new pixel decimation algorithm for the estimation of motion vector is proposed. In traditional methods, the computational cost can be reduced since only part of the pixels are used for motion vector calculation. But these methods limits the accuracy ofmotion vector because of the same reason. We derive a selection criteria of subsampled pixels that can reduce the probablity of false motion vector detection based on stochastic point of view. By using this criteria, a new pixel decimation algorithm that can reduce the prediction error with similar computational cost is presented. The simulation results applied to standard images haveshown that the proposed algorithm has less mean absolute prediction error than conventional pixel decimation algorithm.

• Journal of Information Display
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• v.10 no.2
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• pp.80-86
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• 2009

The variation of the electrical characteristics of thin-film transistors (TFTs) causes a non-uniform image quality problem, and the differential aging of organic light-emitting diode (OLED) devices causes an image-sticking problem. A video data correction method is proposed herein as an effective solution to the non-uniform electro-optical characteristics of the pixels in activematrix organic light-emitting diode (AMOLED) displays. The results of the simulation that was conducted show that the proposed method successfully senses the electrical characteristics of TFTs and the degradation of OLEDs and effectively compensates for them.